Artificial Intelligence-Aided Automated Detection of Railroad Trespassing

Abstract

Trespassing is the leading cause of rail-related deaths and has been on the rise for the past 10 years. Detection of unsafe trespassing of railroad tracks is critical for understanding and preventing fatalities. Witnessing these events has become possible with the widespread deployment of large volumes of surveillance video data in the railroad industry. This potential source of information requires immense labor to monitor in real time. To address this challenge this paper describes an artificial intelligence (AI) framework for the automatic detection of trespassing events in real time. This framework was implemented on three railroad video live streams, a grade crossing and two right-of-ways, in the United States. The AI algorithm automatically detects trespassing events, differentiates between the type of violator (car, motorcycle, truck, pedestrian, etc.) and sends an alert text message to a designated destination with important information including a video clip of the trespassing event. In this study, the AI has analyzed hours of live footage with no false positives or missed detections yet. This paper and its subsequent studies aim to provide the railroad industry with state-of-the-art AI tools to harness the untapped potential of an existing closed-circuit television infrastructure through the real-time analysis of their data feeds. The data generated from these studies will potentially help researchers understand human factors in railroad safety research and give them a real-time edge on tackling the critical challenges of trespassing in the railroad industry.

Onboard Sensor Systems for Automatic Train Operation

“…VIII. Developers of CV systems that work in related fields of research like visual infrastructure inspection [22], automated security surveillance [23], train door operation, digital railway mapping etc. performed onboard and off-board might take advantage of these extensions and contribute to the development of further datasets.…”

Intelligent and efficient? An empirical analysis of human–AI collaboration for truck drivers in retail logistics

“…In addition to these efficiency- and effectiveness-centred approaches, AI is used to enhance the security of roads. For example, salt de-icing trucks have been equipped with AI components to decide whether salt on icy roads will work (Berg, 2018), and AI has been used to automatically detect unsafe trespassing of railroad tracks through railroad video live streams (Zaman et al , 2019). Second, AI has been applied to trucks involved in freight transport systems.…”

Amtrak Rail Trespasser Analysis using a GIS Space-Time Approach

“…Video analytics as well as elaborate detection algorithms may lead to more effective detection of trespasser activity (Havarneau & Topel, 2019). Also, overall wider availability of video data through closed circuit television cameras can provide easier access to trespasser data (Zaman et al, 2019). Artificial intelligence algorithms are used to watch for and recognize trespassing events in real time and the more access to this recognition, the more opportunity for live sound alert systems as well as other intervention methods (call systems or lighting).…”